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变电站巡检机器人航向信息融合算法研究 被引量:3

Research on Heading Information Fusion Algorithm for Substation Inspection Robot
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摘要 随着自动化、人工智能等技术的进步发展,巡检机器人已逐步代替人工,实现高可靠性、高安全性、高效率的变电站常规巡检工作。在变电站巡检机器人设计和研发中,实时定位系统是其实现智能导航和精准控制的核心传感单元。考虑到巡检机器人在近似的二维平面中行驶,连续精确的航向输出对其定位导航至关重要。GPS基于全球卫星定位,可提供基于地球坐标系的全局位置、航向等信息,但卫星信号容易受到干扰,且存在较大的随机游走噪声。陀螺仪等器件通过内部惯性传感器感受载体位置变化,通过角速率积分获得相对航向变化,不受外界环境干扰,但存在累积误差。针对两种传感器单独使用时优缺点明显,且具有互补性的特点,提出一种融合GPS和陀螺仪的实时航向算法。通过设计一种基于航向误差的自适应离散卡尔曼滤波器,实时融合两种传感器的航向输出。试验结果表明,该融合算法能够有效降低GPS的随机噪声和陀螺仪的累积误差,为巡检机器人提供高可靠性、高精度的实时航向。 With the development of technologies such as automation and artificial intelligence,inspection robots have gradually replaced manual labor to achieve high⁃reliability,high⁃safety,and high⁃efficiency routine inspection in substations.In the design and development of substation inspection robot,real⁃time positioning system is the core sensor unit to realize intelligent navigation and precise control.Considering that the inspection robot travels in an approximate two⁃dimensional plane,continuous and accurate heading output is very important for its positioning and navigation.GPS is based on global satellite positioning,which can provide global position,heading and other information based on the earth coordinate system.However,the satellite signal is easy to be interfered and has large random walk noise.Gyroscope and other devices sense the position change of the carrier through the internal inertial sensor,and obtain the relative heading change through the angular rate integration,which is not affected by the external environment,but there is a cumulative error.Considering that the obvious advantages and disadvantages of the two sensors when used alone,and the characteristics of complementarity,a real⁃time heading algorithm combining GPS and gyroscope was proposed.An adaptive discrete Kalman filter based on heading error was designed to fuse the heading outputs of the two sensors in real time.The experimental results show that the fusion algorithm can effectively reduce the random noise of GPS and the accumulated error of gyroscope,and provide high reliability and high precision real⁃time heading for inspection robot.
作者 张蒙 高嵩 李琛 ZHANG Meng;GAO Song;LI Chen(State Grid Shandong Electric Power Research Institute,Jinan 250003,China;State Grid Yucheng Power Supply Comply,Yucheng 251200,China)
出处 《山东电力技术》 2021年第9期6-11,22,共7页 Shandong Electric Power
关键词 巡检机器人 组合导航 航向融合 卡尔曼滤波 inspection robot integrated navigation heading fusion Kalman filter
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